Competitive base pyy; incentive compensation subje...
Fully remote
Time-series forecasting expertise
Econometrics and machine learning modeling
Python and sql proficiency
The role involves designing and evaluating statistical, econometric, and machine learning methods to increase forecast accuracy and accelerate delivery timelines
Job Summary
The role involves designing and evaluating statistical, econometric, and machine learning methods to increase forecast accuracy and accelerate delivery timelines.
Candidates will own the end-to-end modeling lifecycle including scoping, feature engineering, deployment, monitoring, and model explainability.
Zillow Group is a strategic organization focused on delivering exceptional experiences and measurable outcomes in the real estate market.
Matching Summary
The role involves designing and evaluating statistical, econometric, and machine learning methods to increase forecast accuracy and accelerate delivery timelines.
Salary
Competitive base pay; Incentive compensation subject to laws and policies; Amounts vary by experience, performance, and location
Skills & Requirements
Must-have
Time-series forecasting expertise
Econometrics and machine learning modeling
Python and SQL proficiency
Data engineering principles at scale
End-to-end model lifecycle ownership
Nice-to-have
Experience with noisy real-world data
Cross-functional partnership skills
Ability to explain complex models to non-technical audiences
Key Requirements
Advanced degree (Masters or PhD) in quantitative discipline
3+ years of experience in applied scientist roles
Strong background in time-series forecasting and nowcasting